EVI-2 Manuscript

Section

Cumulative Clonal Growth Rates

Growth rate, 𝛼 = log (𝑉𝐴𝐹 𝑓𝑜𝑙𝑙𝑜𝑤-𝑢𝑝/𝑉𝐴𝐹 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 )/𝑡𝑖𝑚𝑒 Patients 14 and 96 have no VAF info because they did not have nay VAFS, therefore their growth rate is 0

patients being removed from VAF analysis due to no follow-up visit

EVI2	…2	…3	…4	ID	visit
17	1	Baseline	43174	17	1
21	1	Baseline	43243	21	1
32	1	Baseline	43502	32	1
43	1	Baseline	43679	43	1
48	1	Baseline	43781	48	1
76	1	Baseline	44088	76	1
82	1	Baseline	44091	82	1
87	1	Baseline	44266	87	1
USC-60-1	1	Baseline	44550	USC60	1

Missing baseline and FU

ID	visit_1	AF_1	Time_1	Hugo_Symbol	cDNA_Change	visit_FU	AF_FU	Time_FU

Cumulative

All patients

Accounting: 109 patients, 9 with only a follow-up time, 3 without any VAF info, and 1 without either for a total of 11 patients excluded (8 no follow-up only, 2 no VAFS info only, 1 missing both)

	Placebo (N=51)	Vitamin C (N=49)	Overall (N=100)
GR
Mean (SD)	0.843 (3.25)	0.450 (1.98)	0.650 (2.70)
Median [Min, Max]	0.201 [-2.70, 18.4]	0.0404 [-4.69, 9.66]	0.111 [-4.69, 18.4]

emmeans and contrast

Treatment_arm emmean SE df asymp.LCL asymp.UCL Placebo 0.3057725 0.1484876 NA 0.0147422 0.5968028 Vitamin C 0.1964945 0.1514876 NA -0.1004157 0.4934048

contrast estimate SE df asymp.LCL asymp.UCL Placebo - Vitamin C 0.109278 0.2121251 NA -0.3064795 0.5250355

p-value on difference

model term	df1	df2	F.ratio	Chisq	p.value
Treatment_arm	1	Inf	0.265	0.265	0.6064424

FC

Treatment_arm response SE df asymp.LCL asymp.UCL Placebo 0.3736240 0.1075241 NA 0.2114759 0.6544847 Vitamin C 0.5695938 0.1867436 NA 0.2982257 1.0798801

contrast estimate SE df asymp.LCL asymp.UCL Placebo - Vitamin C -0.5953494 0.6161018 NA -1.802887 0.6121879

Subgroups

TET2 mutation status

Median baseline vitamin C mutation status

Baseline diagnosis

Individual mutations

## 
##   FLT3   GNB1   NRAS   PHF6  PPM1D SETBP1   BCOR   BRAF  ETNK1   ETV6  GATA2 
##      1      1      1      1      1      1      2      2      2      2      2 
##   JAK2    KIT    MPL  CEBPA   EZH2   IDH2    NF1 PTPN11   IDH1    CBL   KRAS 
##      2      2      2      3      3      3      3      3      4      6      6 
##  SH2B3  STAG2   TP53  U2AF1  RUNX1  SF3B1  ASXL1  ZRSR2  SRSF2 DNMT3A   TET2 
##      6      7      7      7     14     21     24     26     27     31    108

TET2

DNMT3A

SRSF2

ASXL1

ZRSR2

Emergence of a new mutation

Treatment_arm emmean SE df asymp.LCL asymp.UCL Placebo -1.085708 0.3263456 Inf -1.725334 -0.4460830 Vitamin C -1.114014 0.3354149 Inf -1.771416 -0.4566132

contrast estimate SE df z.ratio p.value Placebo - Vitamin C 0.0283058 0.4734656 Inf 0.0597842 0.9523275

model term	df1	df2	F.ratio	Chisq	p.value
Treatment_arm	1	Inf	0.004	0.004	0.9523275
time	1	Inf	0.063	0.063	0.8010501

	Placebo (N=51)	Vitamin C (N=49)	Overall (N=100)
Emergent
Mean (SD)	0.255 (0.440)	0.245 (0.434)	0.250 (0.435)
Median [Min, Max]	0 [0, 1.00]	0 [0, 1.00]	0 [0, 1.00]
time
Mean (SD)	0.920 (0.296)	1.03 (0.181)	0.972 (0.251)
Median [Min, Max]	1.02 [0.235, 1.43]	1.02 [0.249, 1.33]	1.02 [0.235, 1.43]

Progress, stable, Contracting clones

Each defined as: averaging >10% over 1 year is an expanding clones, <10% contracting clones, within +/-10% stable.

Manuscript figure

Plasma Vitamin C

Figure 3

Figure 3: Patient plasma vitamin C level. A) Composition of all patients, placebo controls, and vitamin C treated individuals with: vitamin C deficiency, inadequate vitamin C, or adequate vitamin C at inclusion; distributions are relatively similar between the two treatment arms. B) Plasma vitamin C level at each timepoint by treatment arm; p-values were estimated using robust linear mixed-effects model with a random intercept for each individual. C) LOESS smoothed vitamin C level over time with standard error ribbons. Individuals with >200 /L vitamin C level were censored in C) to better characterize dispersion among trial participants, all individual measures are shown in panel B).

Supplemental figure, Vitamin C change over time

Supplemental figure xx. Change in vitamin C over time. On average patients treated with vitamin C had a ~2.1 fold increase in plasma vitamin C level between their measures at inclusion and those taken at End of treatment (95% CI 1.6 - 2.8), while those on placebo had no real change. robust linear mixed-effects model with ratio of vitamin C at EOT divided by vitamin C at inclusion.

	Placebo (N=54)	Vitamin C (N=55)	Overall (N=109)
Baseline Vitamin C
Mean (SD)	43.66 (24.55)	47.64 (25.17)	45.67 (24.83)
Median (Min, Max)	43.75 (22.20, 60.39)	45.85 (29.80, 69.12)	44.18 (27.33, 63.32)
EOT Vitamin C
Mean (SD)	45.31 (31.09)	83.22 (24.40)	65.12 (33.56)
Median (Min, Max)	48.73 (20.56, 58.21)	81.90 (67.08, 99.57)	63.82 (47.69, 87.34)
Missing	12 (22.2%)	9 (16.4%)	21 (19.3%)

change in vitamin C

Treatment_arm	emmean	SE	df	z.ratio	p.value
Placebo	-0.7534369	4.882218	NA	-0.1543227	0.8773553
Vitamin C	36.8381243	4.665120	NA	7.8965003	0.0000000

Treatment_arm response SE df asymp.LCL asymp.UCL Placebo 0.9257738 0.0960257 NA 0.7554647 1.134477 Vitamin C 1.9340593 0.1916894 NA 1.5925941 2.348737

contrast ratio SE df asymp.LCL asymp.UCL Placebo / Vitamin C 0.4786688 0.0686721 NA 0.3613414 0.6340922

Supplemental figure, plasma versus bone marrow vitamin C

Correlate Vitamin C in plasma and bone marrow

Survival

Includes all samples, unadjusted. We also performed a landmark analysis and also analyzed this same data with peto-peto. Both were still significant, therefore an FDR correction would not change our findings here.

Primary outcome KM (Figure 3)

Figure 4. Unadjusted Kaplan-Meier curves for overall survival. Estimated hazard ratio for vitamin C treated patients versus controls based on an unadjusted Cox proportional hazards regression 0.35, 95% CI 0.17, 0.71.

	Placebo (N=54)	Vitamin C (N=55)	Overall (N=109)
Follow up (Months)
Mean (sd)	30.6 (17.0)	39.3 (17.8)	35.0 (17.9)
Median [Q1, Q3]	28.1 [18.2, 41.2]	36.4 [25.8, 49.5]	33.6 [21.4, 48.3]
Event
Censored	30 (55.6%)	44 (80.0%)	74 (67.9%)
Died	24 (44.4%)	11 (20.0%)	35 (32.1%)

Hazard ratio and CI

	exp(coef)	exp(-coef)	lower .95	upper .95
Treatment_armVitamin C	0.3473816	2.878679	0.1697418	0.7109265

Cox model (No interaction)

Supplemntal figure XX. Forest plot for adjusted Cox model. Cox proportional hazards regression to estimated efficacy of vitamin C on overall survival was adjusted for patient age at inclusion, gender, hemoglobin levels at inclusion, and whether or not they had been diagnosed with CCUS.

Cox model (Age interaction)

Supplemental figure XX. Forest plot for adjusted Cox model in age interaction. Cox proportional hazards regression to estimated efficacy of vitamin C as a function of age. Age was mean centered and converted to decades to improve hazard ratio scales. Overall vitamin C was still effective, with evidence that it’s efficacy decreases with age.

Cox model (TET interaction)

	Placebo	Vitamin C
TET2Mut	32	31
TET2neg	22	24

Cox model (Hb1 interaction)

Cox model (Sex interaction)

Cox model (CCUS interaction)

Forest plot cannot be made due to diverging SE in treatment

## Call:
## coxph(formula = Surv(Days_FU_OS, FU_Death) ~ VitaminC + age_c + 
##     vitc_ccus + Male + Hb1_c + CCUS, data = df)
## 
##                       coef        exp(coef)         se(coef)      z        p
## VitaminC    -0.48013788583    0.61869807622    0.39738120115 -1.208 0.226949
## age_c        0.04289957950    1.04383306735    0.02439246075  1.759 0.078625
## vitc_ccus  -18.85453900918    0.00000000648 5424.03021304527 -0.003 0.997226
## Male         0.84285200671    2.32298270049    0.46551028687  1.811 0.070203
## Hb1_c       -0.67791720098    0.50767327337    0.18565236465 -3.652 0.000261
## CCUS         0.23284559292    1.26218657373    0.51029109759  0.456 0.648175
## 
## Likelihood ratio test=40.98  on 6 df, p=0.0000002919
## n= 109, number of events= 35

Cox model (baseline vitamin C interaction)

2-year landmark

Maybe Figure? A 2 year landmark analysis was performed to determine if there was still evidence of vitamin C efficacy after removing individuals who had events prior to 2 years. This landmark analysis ensures the effects of vitamin C had sufficient time to reach efficacy.

Per patient protocol

likelihood ratio test p-value is nearly identical to log-rank

LRT on treatment

#Df	LogLik	Df	Chisq	Pr(>Chisq)
1	-76.00080	NA	NA	NA
0	-77.16977	-1	2.337937	0.1262567

Subgroups (suppl)

All subgroup analyses include only the hazard ratio with 95% CI as these are exploratory.

TET1 or IDH1/2 at baseline

Supplemental Figure XX. Overall survival by TET2 or IDH1/2 mutation status. Hazard ratio and confidence intervals were estimated using Cox proportional hazards models on data stratified by TET2 and IDH1/2 mutation status. Survival curves and estimates are consistent with the primary outcome.

LRT for interaction

#Df	LogLik	Df	Chisq	Pr(>Chisq)
3	-142.8280	NA	NA	NA
2	-143.5895	-1	1.523109	0.2171495

Manuscript Figure

LOF TET2

AKA TET2 hypermethylation vs WT signature

LRT for interaction

#Df	LogLik	Df	Chisq	Pr(>Chisq)
3	-107.0926	NA	NA	NA
2	-107.8713	-1	1.557548	0.2120246

Above/Below median Vitamin C

Supplemental figure XX. Overall survival by vitamin C above or below median vitamin C at inclusion. Hazard ratio and confidence intervals were estimated using Cox proportional hazards models on data stratified by patients with plasma vitamin C level below the median measure at inclusion, and greater than or equal to the median. Results are consistent with the primary outcome.

LRT for interaction

#Df	LogLik	Df	Chisq	Pr(>Chisq)
3	-142.7831	NA	NA	NA
2	-142.7974	-1	0.0284974	0.8659447

Diagnostic subgroup

Supplemental figure XX. Overall survival by diagnostic subgroup at inclusion. Hazard ratio and confidence intervals were estimated using Cox proportional hazards models on data stratified by diagnosis at inclusion. CCUS appears to be a subgroup that can benefit particularly well from vitamin C supplementation.

LRT for interaction

#Df	LogLik	Df	Chisq	Pr(>Chisq)
11	-134.4270	NA	NA	NA
6	-138.5647	-5	8.275447	0.1416943

Competing risk regression (progression)

For this analysis death is a competing risk of high-risk progression. We are a bit limited in sample size and events; there are only 14 progression events. Power to detect any differences in progression is quite low and we will have difficulty adjusting for any covariates here. We see corroboration with out overall survival findings that death (the dotted lines) are significantly different, however we do not have enough evidence to determine if progression also differs (p = 0.22).

Because competing risks comes from a different package, I can’t seem to add a y-axis title to the risk table

Global Methylation

Figure XX. Global methylation changes over time by treatment arm A) 5-mC/dG and B) 5-hmC/5-mC level for each patient at inclusion and end-of-therapy (EOT) and the change in these measures between inclusion and EOT. Data were analyzed using robust linear mixed-effects models with a random intercept for each patient and an interaction between treatment and time point to assess if measures changed differently over time. Models also included a covariate for batch.

IDs not in Mass Spec data

x
75
79
6
5
4
26
47
23
93

IDs not in methylation data

x
12
17
21
43
48
76
USC52
USC54
USC57
32
87
USC53
USC59

Delta 5-mC and 5-hmC/5-mC

TET2

baseline vitamin C

Diagnosis

Baseline 5-mC and 5-hmC/5-mC

The raw p-values should be printing in each section

Saved p-values and FDR adjustments

outcome	subgroup	p	FDR
mC.dG	TET2	0.1991000	0.2844286
mC.dG	vitc_med	0.1066000	0.2132000
mC.dG	vitc_ccus	0.0078000	0.0390000
mC.dG	vitc_ccus	0.6186000	0.6873333
mC.dG	vitc_ccus	0.0797000	0.2092500
hmC.mC	TET2	0.0000001	0.0000009
hmC.mC	vitc_med	0.5790000	0.6873333
hmC.mC	vitc_ccus	0.7838000	0.7838000
hmC.mC	vitc_ccus	0.1405000	0.2341667
hmC.mC	vitc_ccus	0.0837000	0.2092500

TET2

##  contrast                                                  estimate       SE df
##  (No TET2 or IDH1/2 mutation) - (TET2 or IDH1/2 mutation) -0.000977 0.000761 NA
##  z.ratio p.value
##   -1.284  0.1991
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

##  contrast                                                 estimate       SE df
##  (No TET2 or IDH1/2 mutation) - (TET2 or IDH1/2 mutation)  0.00285 0.000533 NA
##  z.ratio p.value
##    5.349  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

baseline vitamin C

##  contrast                    estimate       SE df z.ratio p.value
##  Below median - Above median -0.00119 0.000737 NA  -1.614  0.1066
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

##  contrast                     estimate       SE df z.ratio p.value
##  Below median - Above median -0.000329 0.000593 NA  -0.555  0.5790
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Diagnosis

##  contrast          estimate       SE df z.ratio p.value
##  CCUS - MDS        0.002199 0.000827 NA   2.659  0.0078
##  CCUS - (MDS/MPN)  0.000492 0.000989 NA   0.498  0.6186
##  MDS - (MDS/MPN)  -0.001707 0.000974 NA  -1.752  0.0797
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

##  contrast          estimate       SE df z.ratio p.value
##  CCUS - MDS       -0.000178 0.000649 NA  -0.274  0.7838
##  CCUS - (MDS/MPN)  0.001144 0.000776 NA   1.474  0.1405
##  MDS - (MDS/MPN)   0.001322 0.000764 NA   1.730  0.0837
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

5-mC/dG

All corr

##            
##             All
##   Placebo    45
##   Vitamin C  40

TET2

##            
##             No TET2 or IDH1/2 mutation TET2 or IDH1/2 mutation
##   Placebo                           16                      29
##   Vitamin C                         18                      22

##  contrast                                                  estimate       SE df
##  (No TET2 or IDH1/2 mutation) - (TET2 or IDH1/2 mutation) -0.000977 0.000761 NA
##  z.ratio p.value
##   -1.284  0.1991
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                                                  estimate       SE df
##  (No TET2 or IDH1/2 mutation) - (TET2 or IDH1/2 mutation) -0.000663 0.000877 NA
##  z.ratio p.value
##   -0.756  0.4496
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

LOF TET2

##            
##             TET2 WT signature TET2 hypermethylation signature
##   Placebo                  25                              15
##   Vitamin C                21                              14

##  contrast                                            estimate       SE df
##  TET2 WT signature - TET2 hypermethylation signature -0.00165 0.000776 NA
##  z.ratio p.value
##   -2.124  0.0337
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                                            estimate       SE df
##  TET2 WT signature - TET2 hypermethylation signature -0.00245 0.000884 NA
##  z.ratio p.value
##   -2.773  0.0055
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Median Vitamin C

##            
##             Below median Above median
##   Placebo             23           22
##   Vitamin C           19           21

##  contrast                    estimate       SE df z.ratio p.value
##  Below median - Above median -0.00119 0.000737 NA  -1.614  0.1066
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                     estimate       SE df z.ratio p.value
##  Below median - Above median -0.000707 0.000801 NA  -0.883  0.3773
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Vitamin C Severe

##            
##             Severe (< 11.4 μmol/L) All others
##   Placebo                        4         41
##   Vitamin C                      2         38

##  contrast                               estimate      SE df z.ratio p.value
##  (Severe (< 11.4 μmol/L)) - All others 0.0000566 0.00147 NA   0.038  0.9693
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                              estimate      SE df z.ratio p.value
##  (Severe (< 11.4 μmol/L)) - All others -0.00123 0.00162 NA  -0.763  0.4452
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Diagnosis (CCUS)

##            
##             CCUS MDS MDS/MPN
##   Placebo     16  17      11
##   Vitamin C   15  17       7

##  contrast          estimate       SE df z.ratio p.value
##  CCUS - MDS        0.002199 0.000827 NA   2.659  0.0214
##  CCUS - (MDS/MPN)  0.000492 0.000989 NA   0.498  0.8724
##  MDS - (MDS/MPN)  -0.001707 0.000974 NA  -1.752  0.1859
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
## P value adjustment: tukey method for comparing a family of 3 estimates 
##  contrast          estimate       SE df z.ratio p.value
##  CCUS - MDS        0.001813 0.000924 NA   1.961  0.1220
##  CCUS - (MDS/MPN) -0.000129 0.001110 NA  -0.117  0.9925
##  MDS - (MDS/MPN)  -0.001942 0.001090 NA  -1.784  0.1750
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
## P value adjustment: tukey method for comparing a family of 3 estimates

5-hmC/dG

All corr

##            
##             All
##   Placebo    45
##   Vitamin C  40

TET2

##            
##             No TET2 or IDH1/2 mutation TET2 or IDH1/2 mutation
##   Placebo                           16                      29
##   Vitamin C                         18                      22

##  contrast                                                  estimate        SE
##  (No TET2 or IDH1/2 mutation) - (TET2 or IDH1/2 mutation) 0.0000996 0.0000208
##  df z.ratio p.value
##  NA   4.793  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                                                 estimate        SE df
##  (No TET2 or IDH1/2 mutation) - (TET2 or IDH1/2 mutation) 0.000102 0.0000196 NA
##  z.ratio p.value
##    5.206  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

LOF TET2

##            
##             TET2 WT signature TET2 hypermethylation signature
##   Placebo                  25                              15
##   Vitamin C                21                              14

##  contrast                                            estimate        SE df
##  TET2 WT signature - TET2 hypermethylation signature 0.000113 0.0000212 NA
##  z.ratio p.value
##    5.347  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                                            estimate        SE df
##  TET2 WT signature - TET2 hypermethylation signature 0.000105 0.0000187 NA
##  z.ratio p.value
##    5.610  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Median Vitamin C

##            
##             Below median Above median
##   Placebo             23           22
##   Vitamin C           19           21

##  contrast                      estimate        SE df z.ratio p.value
##  Below median - Above median -0.0000222 0.0000221 NA  -1.005  0.3148
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                       estimate        SE df z.ratio p.value
##  Below median - Above median -0.00000218 0.0000219 NA  -0.099  0.9210
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Vitamin C Severe

##            
##             Severe (< 11.4 μmol/L) All others
##   Placebo                        4         41
##   Vitamin C                      2         38

##  contrast                               estimate        SE df z.ratio p.value
##  (Severe (< 11.4 μmol/L)) - All others 0.0000298 0.0000435 NA   0.686  0.4929
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                               estimate        SE df z.ratio p.value
##  (Severe (< 11.4 μmol/L)) - All others 0.0000389 0.0000427 NA   0.910  0.3630
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Diagnosis (CCUS)

##            
##             CCUS MDS MDS/MPN
##   Placebo     16  17      11
##   Vitamin C   15  17       7

##  contrast          estimate        SE df z.ratio p.value
##  CCUS - MDS       0.0000118 0.0000243 NA   0.483  0.8793
##  CCUS - (MDS/MPN) 0.0000476 0.0000291 NA   1.635  0.2309
##  MDS - (MDS/MPN)  0.0000358 0.0000287 NA   1.250  0.4236
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
## P value adjustment: tukey method for comparing a family of 3 estimates 
##  contrast          estimate        SE df z.ratio p.value
##  CCUS - MDS       0.0000258 0.0000241 NA   1.070  0.5325
##  CCUS - (MDS/MPN) 0.0000540 0.0000289 NA   1.870  0.1474
##  MDS - (MDS/MPN)  0.0000282 0.0000284 NA   0.990  0.5830
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
## P value adjustment: tukey method for comparing a family of 3 estimates

5-hmC/5-mC

All corr

##            
##             All
##   Placebo    45
##   Vitamin C  40

TET2

##            
##             No TET2 or IDH1/2 mutation TET2 or IDH1/2 mutation
##   Placebo                           16                      29
##   Vitamin C                         18                      22

##  contrast                                                 estimate       SE df
##  (No TET2 or IDH1/2 mutation) - (TET2 or IDH1/2 mutation)  0.00285 0.000533 NA
##  z.ratio p.value
##    5.349  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                                                 estimate       SE df
##  (No TET2 or IDH1/2 mutation) - (TET2 or IDH1/2 mutation)  0.00292 0.000488 NA
##  z.ratio p.value
##    5.991  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

LOF TET2

##            
##             TET2 WT signature TET2 hypermethylation signature
##   Placebo                  25                              15
##   Vitamin C                21                              14

##  contrast                                            estimate       SE df
##  TET2 WT signature - TET2 hypermethylation signature  0.00333 0.000496 NA
##  z.ratio p.value
##    6.718  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                                            estimate       SE df
##  TET2 WT signature - TET2 hypermethylation signature  0.00322 0.000439 NA
##  z.ratio p.value
##    7.336  <.0001
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Median Vitamin C

##            
##             Below median Above median
##   Placebo             23           22
##   Vitamin C           19           21

##  contrast                     estimate       SE df z.ratio p.value
##  Below median - Above median -0.000329 0.000593 NA  -0.555  0.5790
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                     estimate       SE df z.ratio p.value
##  Below median - Above median 0.0000483 0.000558 NA   0.087  0.9310
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Vitamin C Severe

##            
##             Severe (< 11.4 μmol/L) All others
##   Placebo                        4         41
##   Vitamin C                      2         38

##  contrast                              estimate      SE df z.ratio p.value
##  (Severe (< 11.4 μmol/L)) - All others 0.000792 0.00114 NA   0.697  0.4860
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
##  contrast                              estimate      SE df z.ratio p.value
##  (Severe (< 11.4 μmol/L)) - All others  0.00136 0.00108 NA   1.261  0.2073
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates.

Diagnosis (CCUS)

##            
##             CCUS MDS MDS/MPN
##   Placebo     16  17      11
##   Vitamin C   15  17       7

##  contrast          estimate       SE df z.ratio p.value
##  CCUS - MDS       -0.000178 0.000649 NA  -0.274  0.9593
##  CCUS - (MDS/MPN)  0.001144 0.000776 NA   1.474  0.3036
##  MDS - (MDS/MPN)   0.001322 0.000764 NA   1.730  0.1941
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
## P value adjustment: tukey method for comparing a family of 3 estimates 
##  contrast         estimate       SE df z.ratio p.value
##  CCUS - MDS       0.000511 0.000627 NA   0.815  0.6936
##  CCUS - (MDS/MPN) 0.001464 0.000750 NA   1.953  0.1240
##  MDS - (MDS/MPN)  0.000953 0.000738 NA   1.292  0.3998
## 
## Results are averaged over the levels of: Treatment_arm 
## Note: contrasts are still on the as.numeric scale. Consider using
##       regrid() if you want contrasts of back-transformed estimates. 
## P value adjustment: tukey method for comparing a family of 3 estimates

Manuscript Figure

rlmer estimates 5mC/dG

	Estimate	Std. Error	t value	2.5%	97.5%
(Intercept)	0.0352878	0.0010852	32.5174893	0.0331609	0.0374147
Treatment_armVitamin C	0.0004736	0.0007077	0.6692364	-0.0009135	0.0018608
TimepointEOT	-0.0000521	0.0003274	-0.1590705	-0.0006938	0.0005896
Batch	0.0009001	0.0006899	1.3047354	-0.0004520	0.0022523
Treatment_armVitamin C:TimepointEOT	-0.0004371	0.0004760	-0.9183844	-0.0013700	0.0004957

Time comparisons by treatment 5mC/dG

Timepoint Treatment_arm emmean SE df asymp.LCL asymp.UCL Baseline Placebo 0.0366380 0.0005055 Inf 0.0356473 0.0376287 EOT Placebo 0.0365859 0.0005122 Inf 0.0355819 0.0375899 Baseline Vitamin C 0.0371116 0.0005036 Inf 0.0361245 0.0380987 EOT Vitamin C 0.0366224 0.0005234 Inf 0.0355966 0.0376483

contrast Treatment_arm estimate SE df z.ratio p.value Baseline - EOT Placebo 0.0000521 0.0003274 Inf 0.1590705 0.8736133 Baseline - EOT Vitamin C 0.0004892 0.0003457 Inf 1.4149172 0.1570928

anova on 5mC/dG model

	model term	df1	df2	F.ratio	Chisq	p.value
1	Treatment_arm	1	Inf	0.143	0.143	0.7057041
3	Timepoint	1	Inf	1.291	1.291	0.2558292
4	Batch	1	Inf	1.702	1.702	0.1919830
2	Treatment_arm:Timepoint	1	Inf	0.843	0.843	0.3584176

	Baseline		EOT		Overall
	Placebo (N=48)	Vitamin C (N=48)	Placebo (N=45)	Vitamin C (N=40)	Placebo (N=93)	Vitamin C (N=88)
mC.dG
Mean (SD)	0.0365 (0.00461)	0.0369 (0.00330)	0.0363 (0.00416)	0.0362 (0.00373)	0.0364 (0.00437)	0.0366 (0.00350)
Median [Min, Max]	0.0363 [0.0264, 0.0560]	0.0376 [0.0265, 0.0452]	0.0372 [0.0251, 0.0436]	0.0367 [0.0286, 0.0443]	0.0367 [0.0251, 0.0560]	0.0373 [0.0265, 0.0452]
hmC.mC
Mean (SD)	0.00711 (0.00266)	0.00697 (0.00276)	0.00673 (0.00265)	0.00686 (0.00243)	0.00693 (0.00265)	0.00692 (0.00260)
Median [Min, Max]	0.00617 [0.00206, 0.0130]	0.00634 [0.00342, 0.0138]	0.00616 [0.00161, 0.0128]	0.00666 [0.00370, 0.0146]	0.00616 [0.00161, 0.0130]	0.00651 [0.00342, 0.0146]

rlmer estimates 5hmC/5mC

	Estimate	Std. Error	t value	2.5%	97.5%
(Intercept)	0.0067577	0.0008970	7.5339083	0.0049996	0.0085157
Treatment_armVitamin C	-0.0002895	0.0005735	-0.5047597	-0.0014134	0.0008345
TimepointEOT	-0.0001792	0.0001756	-1.0205230	-0.0005234	0.0001650
Batch	0.0002108	0.0005732	0.3677627	-0.0009127	0.0013343
Treatment_armVitamin C:TimepointEOT	-0.0000737	0.0002557	-0.2884575	-0.0005748	0.0004274

Time comparisons by treatment 5hmC/5mC

Timepoint Treatment_arm emmean SE df asymp.LCL asymp.UCL Baseline Placebo 0.0070739 0.0004098 Inf 0.0062707 0.0078770 EOT Placebo 0.0068947 0.0004123 Inf 0.0060865 0.0077028 Baseline Vitamin C 0.0067844 0.0004082 Inf 0.0059843 0.0075845 EOT Vitamin C 0.0065315 0.0004157 Inf 0.0057168 0.0073461

contrast Treatment_arm estimate SE df z.ratio p.value Baseline - EOT Placebo 0.0001792 0.0001756 Inf 1.020523 0.3074805 Baseline - EOT Vitamin C 0.0002529 0.0001859 Inf 1.360685 0.1736134

anova on 5hmC/5mC model

	model term	df1	df2	F.ratio	Chisq	p.value
1	Treatment_arm	1	Inf	0.337	0.337	0.5616665
3	Timepoint	1	Inf	2.855	2.855	0.0910993
4	Batch	1	Inf	0.135	0.135	0.7130502
2	Treatment_arm:Timepoint	1	Inf	0.083	0.083	0.7729965

	Baseline		EOT		Overall
	Placebo (N=48)	Vitamin C (N=48)	Placebo (N=45)	Vitamin C (N=40)	Placebo (N=93)	Vitamin C (N=88)
mC.dG
Mean (SD)	0.0365 (0.00461)	0.0369 (0.00330)	0.0363 (0.00416)	0.0362 (0.00373)	0.0364 (0.00437)	0.0366 (0.00350)
Median [Min, Max]	0.0363 [0.0264, 0.0560]	0.0376 [0.0265, 0.0452]	0.0372 [0.0251, 0.0436]	0.0367 [0.0286, 0.0443]	0.0367 [0.0251, 0.0560]	0.0373 [0.0265, 0.0452]
hmC.mC
Mean (SD)	0.00711 (0.00266)	0.00697 (0.00276)	0.00673 (0.00265)	0.00686 (0.00243)	0.00693 (0.00265)	0.00692 (0.00260)
Median [Min, Max]	0.00617 [0.00206, 0.0130]	0.00634 [0.00342, 0.0138]	0.00616 [0.00161, 0.0128]	0.00666 [0.00370, 0.0146]	0.00616 [0.00161, 0.0130]	0.00651 [0.00342, 0.0146]

Cytokines

Primary Analysis, all patients

Suppl all cytokines

Supplemental Figure XX. log2 fold-change in cytokine measures for all individuals. Data were analyzed using robust linear mixed-effects models with a random intercept for each patient and an interaction between treatment and timepoint to assess if measures changed differently over time.

Significant changes over time by treatment

assay	contrast	Treatment_arm	estimate	SE	df	z.ratio	p.value	FDR	FoldChange
IL-17	Baseline - EOT	Placebo	-0.1332786	0.0927204	Inf	-1.4374241	0.1505975	0.3576691	1.0967834
IL-17	Baseline - EOT	Vitamin C	0.0602033	0.0951232	Inf	0.6328989	0.5267997	0.6391288	0.9591289
IL-1β	Baseline - EOT	Placebo	-0.0123616	0.1931432	Inf	-0.0640020	0.9489686	0.9622531	1.0086052
IL-1β	Baseline - EOT	Vitamin C	-0.1029296	0.1975339	Inf	-0.5210731	0.6023158	0.6935758	1.0739521
IL-4	Baseline - EOT	Placebo	-0.2514464	0.1789781	Inf	-1.4048999	0.1600511	0.3577612	1.1904000
IL-4	Baseline - EOT	Vitamin C	-0.0666618	0.1834156	Inf	-0.3634466	0.7162713	0.7776660	1.0472906
IL-12p70	Baseline - EOT	Placebo	0.0640389	0.0760567	Inf	0.8419881	0.3997946	0.6391288	0.9565824
IL-12p70	Baseline - EOT	Vitamin C	0.1923900	0.0779515	Inf	2.4680741	0.0135842	0.0516200	0.8751547
IL-6	Baseline - EOT	Placebo	-0.4362539	0.0826185	Inf	-5.2803436	0.0000001	0.0000024	1.3530863
IL-6	Baseline - EOT	Vitamin C	0.0527016	0.0847573	Inf	0.6217949	0.5340767	0.6391288	0.9641292
TNF-α	Baseline - EOT	Placebo	-0.1320412	0.0597960	Inf	-2.2081947	0.0272307	0.0940697	1.0958431
TNF-α	Baseline - EOT	Vitamin C	0.0536337	0.0613551	Inf	0.8741518	0.3820356	0.6391288	0.9635065
RANTES	Baseline - EOT	Placebo	0.0599012	0.0955209	Inf	0.6271011	0.5305930	0.6391288	0.9593298
RANTES	Baseline - EOT	Vitamin C	-0.3104729	0.0980393	Inf	-3.1668217	0.0015411	0.0065071	1.2401141
TGF-β1	Baseline - EOT	Placebo	-0.0262872	0.0427075	Inf	-0.6155164	0.5382137	0.6391288	1.0183879
TGF-β1	Baseline - EOT	Vitamin C	-0.1647981	0.0437725	Inf	-3.7648811	0.0001666	0.0012122	1.1210092
IL-7	Baseline - EOT	Placebo	-0.0415905	0.0498705	Inf	-0.8339697	0.4042981	0.6391288	1.0292479
IL-7	Baseline - EOT	Vitamin C	-0.0364320	0.0508352	Inf	-0.7166687	0.4735785	0.6391288	1.0255743
VEGF_cyto	Baseline - EOT	Placebo	-0.0796990	0.0440505	Inf	-1.8092665	0.0704096	0.2058127	1.0567975
VEGF_cyto	Baseline - EOT	Vitamin C	-0.0491262	0.0448852	Inf	-1.0944856	0.2737421	0.5201099	1.0346381
IFN-γ	Baseline - EOT	Placebo	-0.0896462	0.0920383	Inf	-0.9740099	0.3300516	0.5972363	1.0641092
IFN-γ	Baseline - EOT	Vitamin C	0.1293656	0.0944258	Inf	1.3700247	0.1706792	0.3603227	0.9142334
IL-10	Baseline - EOT	Placebo	-0.2673398	0.0710773	Inf	-3.7612526	0.0001691	0.0012122	1.2035865
IL-10	Baseline - EOT	Vitamin C	0.1065942	0.0729366	Inf	1.4614651	0.1438879	0.3576691	0.9287780
G-CSF	Baseline - EOT	Placebo	-0.1752064	0.0522099	Inf	-3.3558058	0.0007913	0.0037589	1.1291259
G-CSF	Baseline - EOT	Vitamin C	0.1878973	0.0528796	Inf	3.5533066	0.0003804	0.0020651	0.8778843
M-CSF	Baseline - EOT	Placebo	-0.2519572	0.0329444	Inf	-7.6479618	0.0000000	0.0000000	1.1908216
M-CSF	Baseline - EOT	Vitamin C	-0.0494083	0.0333726	Inf	-1.4805080	0.1387377	0.3576691	1.0348404
SDF-1α	Baseline - EOT	Placebo	-0.1120307	0.0300342	Inf	-3.7301081	0.0001914	0.0012122	1.0807484
SDF-1α	Baseline - EOT	Vitamin C	-0.0339566	0.0304178	Inf	-1.1163426	0.2642755	0.5201099	1.0238161
IL-8_HA	Baseline - EOT	Placebo	-0.0072887	0.1540099	Inf	-0.0473264	0.9622531	0.9622531	1.0050649
IL-8_HA	Baseline - EOT	Vitamin C	0.0257930	0.1553527	Inf	0.1660287	0.8681344	0.9163641	0.9822805
IP-10	Baseline - EOT	Placebo	-0.2078998	0.0479349	Inf	-4.3371247	0.0000144	0.0001829	1.1550056
IP-10	Baseline - EOT	Vitamin C	0.0195322	0.0492476	Inf	0.3966122	0.6916534	0.7730244	0.9865526
GM-CSF	Baseline - EOT	Placebo	-0.1278652	0.1619535	Inf	-0.7895179	0.4298094	0.6391288	1.0926756
GM-CSF	Baseline - EOT	Vitamin C	0.1078128	0.1630296	Inf	0.6613082	0.5084147	0.6391288	0.9279939
IL-1α	Baseline - EOT	Placebo	0.1216627	0.1874807	Inf	0.6489344	0.5163808	0.6391288	0.9191278
IL-1α	Baseline - EOT	Vitamin C	-0.3524563	0.1887263	Inf	-1.8675523	0.0618245	0.1957776	1.2767325

Cytokines that changed differently over time for Placebo versus Vitamin C

	assay	p	est	se	FDR
5	IL-6	0.0000361	0.4889555	0.1183622	0.0002287
7	RANTES	0.0068131	-0.3703742	0.1368793	0.0215747
12	IL-10	0.0002409	0.3739341	0.1018417	0.0011444
13	G-CSF	0.0000010	0.3631036	0.0743110	0.0000195
14	M-CSF	0.0000157	0.2025489	0.0468941	0.0001487
17	IP-10	0.0009352	0.2274320	0.0687247	0.0035539

Cytokine figure

Supplemental Figure XX. log2 fold-change in cytokine measures that changed significantly. Data were analyzed using robust linear mixed-effects models with a random intercept for each patient and an interaction between treatment and timepoint to assess if measures changed differently over time. Larger points indicate the mean log2(fold-change) with 95% CI error bars. Scales were limited to +/-1.5 log2(fold-change) to better characterize dispersion, all data points are shown in supplemental figure XX. P-values were false discovery rate adjusted using Benjamini-Hochberg.

	assay	Treatment_arm	FoldChange	FC.CI	Median change	IQR
7	IL-6	Placebo	1.5469015	1.32, 1.82	978.7228275	4825.271944
8		Vitamin C	0.9486630	0.8, 1.12	-305.2321957	2914.539854
5	IL-10	Placebo	1.3064843	1.14, 1.5	48.3126753	560.975421
6		Vitamin C	0.8988903	0.78, 1.04	-48.4402901	366.301656
3	G-CSF	Placebo	1.1914921	1.08, 1.32	0.3595211	7.581336
4		Vitamin C	0.8286998	0.75, 0.92	-0.9363409	5.804647
9	M-CSF	Placebo	1.2865410	1.21, 1.37	1.9633393	3.361131
10		Vitamin C	1.0506493	0.98, 1.12	0.4335928	3.483504
1	CXCL10 (IP-10)	Placebo	1.2310898	1.12, 1.35	97.4263341	380.265155
2		Vitamin C	0.9806573	0.89, 1.08	-26.4342630	342.846245
11	RANTES (CCL5)	Placebo	0.9418575	0.78, 1.14	-47.1448291	2897.441686
12		Vitamin C	1.3640701	1.13, 1.65	337.3523208	3489.165477

Volcano plots of each subroup by assay

Subgroup plots

All FDR p-values less than 0.1 are shown for comparing across subgroups.

All subgroups

TET2

## 
## 
## |Var1      |Var2           |Var3                        | Freq|
## |:---------|:--------------|:---------------------------|----:|
## |Placebo   |G-CSF          |No TET2 or IDH1/2 mutations |   21|
## |Vitamin C |G-CSF          |No TET2 or IDH1/2 mutations |   23|
## |Placebo   |IL-10          |No TET2 or IDH1/2 mutations |   21|
## |Vitamin C |IL-10          |No TET2 or IDH1/2 mutations |   23|
## |Placebo   |IL-6           |No TET2 or IDH1/2 mutations |   21|
## |Vitamin C |IL-6           |No TET2 or IDH1/2 mutations |   23|
## |Placebo   |CXCL10 (IP-10) |No TET2 or IDH1/2 mutations |   21|
## |Vitamin C |CXCL10 (IP-10) |No TET2 or IDH1/2 mutations |   23|
## |Placebo   |M-CSF          |No TET2 or IDH1/2 mutations |   21|
## |Vitamin C |M-CSF          |No TET2 or IDH1/2 mutations |   23|
## |Placebo   |TGF-β1         |No TET2 or IDH1/2 mutations |   21|
## |Vitamin C |TGF-β1         |No TET2 or IDH1/2 mutations |   23|
## |Placebo   |TNF-α          |No TET2 or IDH1/2 mutations |   21|
## |Vitamin C |TNF-α          |No TET2 or IDH1/2 mutations |   23|
## |Placebo   |VEGF           |No TET2 or IDH1/2 mutations |   21|
## |Vitamin C |VEGF           |No TET2 or IDH1/2 mutations |   23|
## |Placebo   |G-CSF          |TET2 or IDH1/2 mutation     |   32|
## |Vitamin C |G-CSF          |TET2 or IDH1/2 mutation     |   31|
## |Placebo   |IL-10          |TET2 or IDH1/2 mutation     |   32|
## |Vitamin C |IL-10          |TET2 or IDH1/2 mutation     |   31|
## |Placebo   |IL-6           |TET2 or IDH1/2 mutation     |   32|
## |Vitamin C |IL-6           |TET2 or IDH1/2 mutation     |   31|
## |Placebo   |CXCL10 (IP-10) |TET2 or IDH1/2 mutation     |   32|
## |Vitamin C |CXCL10 (IP-10) |TET2 or IDH1/2 mutation     |   31|
## |Placebo   |M-CSF          |TET2 or IDH1/2 mutation     |   32|
## |Vitamin C |M-CSF          |TET2 or IDH1/2 mutation     |   31|
## |Placebo   |TGF-β1         |TET2 or IDH1/2 mutation     |   32|
## |Vitamin C |TGF-β1         |TET2 or IDH1/2 mutation     |   31|
## |Placebo   |TNF-α          |TET2 or IDH1/2 mutation     |   32|
## |Vitamin C |TNF-α          |TET2 or IDH1/2 mutation     |   31|
## |Placebo   |VEGF           |TET2 or IDH1/2 mutation     |   32|
## |Vitamin C |VEGF           |TET2 or IDH1/2 mutation     |   31|

Median Vitamin C

## 
## 
## |Var1      |Var2           |Var3                   | Freq|
## |:---------|:--------------|:----------------------|----:|
## |Placebo   |G-CSF          |Below median vitamin C |   28|
## |Vitamin C |G-CSF          |Below median vitamin C |   26|
## |Placebo   |IL-10          |Below median vitamin C |   28|
## |Vitamin C |IL-10          |Below median vitamin C |   26|
## |Placebo   |IL-6           |Below median vitamin C |   28|
## |Vitamin C |IL-6           |Below median vitamin C |   26|
## |Placebo   |CXCL10 (IP-10) |Below median vitamin C |   28|
## |Vitamin C |CXCL10 (IP-10) |Below median vitamin C |   26|
## |Placebo   |M-CSF          |Below median vitamin C |   28|
## |Vitamin C |M-CSF          |Below median vitamin C |   26|
## |Placebo   |RANTES (CCL5)  |Below median vitamin C |   28|
## |Vitamin C |RANTES (CCL5)  |Below median vitamin C |   26|
## |Placebo   |TGF-β1         |Below median vitamin C |   28|
## |Vitamin C |TGF-β1         |Below median vitamin C |   26|
## |Placebo   |G-CSF          |Above median vitamin C |   25|
## |Vitamin C |G-CSF          |Above median vitamin C |   28|
## |Placebo   |IL-10          |Above median vitamin C |   25|
## |Vitamin C |IL-10          |Above median vitamin C |   28|
## |Placebo   |IL-6           |Above median vitamin C |   25|
## |Vitamin C |IL-6           |Above median vitamin C |   28|
## |Placebo   |CXCL10 (IP-10) |Above median vitamin C |   25|
## |Vitamin C |CXCL10 (IP-10) |Above median vitamin C |   28|
## |Placebo   |M-CSF          |Above median vitamin C |   25|
## |Vitamin C |M-CSF          |Above median vitamin C |   28|
## |Placebo   |RANTES (CCL5)  |Above median vitamin C |   25|
## |Vitamin C |RANTES (CCL5)  |Above median vitamin C |   28|
## |Placebo   |TGF-β1         |Above median vitamin C |   25|
## |Vitamin C |TGF-β1         |Above median vitamin C |   28|

Diagnosis

## 
## 
## |Var1      |Var2           |Var3    | Freq|
## |:---------|:--------------|:-------|----:|
## |Placebo   |G-CSF          |CCUS    |   17|
## |Vitamin C |G-CSF          |CCUS    |   20|
## |Placebo   |IL-10          |CCUS    |   17|
## |Vitamin C |IL-10          |CCUS    |   20|
## |Placebo   |IL-1α          |CCUS    |   17|
## |Vitamin C |IL-1α          |CCUS    |   20|
## |Placebo   |IL-6           |CCUS    |   17|
## |Vitamin C |IL-6           |CCUS    |   20|
## |Placebo   |CXCL10 (IP-10) |CCUS    |   17|
## |Vitamin C |CXCL10 (IP-10) |CCUS    |   20|
## |Placebo   |M-CSF          |CCUS    |   17|
## |Vitamin C |M-CSF          |CCUS    |   20|
## |Placebo   |SDF-1α         |CCUS    |   17|
## |Vitamin C |SDF-1α         |CCUS    |   20|
## |Placebo   |G-CSF          |MDS     |   21|
## |Vitamin C |G-CSF          |MDS     |   18|
## |Placebo   |IL-10          |MDS     |   21|
## |Vitamin C |IL-10          |MDS     |   18|
## |Placebo   |IL-1α          |MDS     |   21|
## |Vitamin C |IL-1α          |MDS     |   18|
## |Placebo   |IL-6           |MDS     |   21|
## |Vitamin C |IL-6           |MDS     |   18|
## |Placebo   |CXCL10 (IP-10) |MDS     |   21|
## |Vitamin C |CXCL10 (IP-10) |MDS     |   18|
## |Placebo   |M-CSF          |MDS     |   21|
## |Vitamin C |M-CSF          |MDS     |   18|
## |Placebo   |SDF-1α         |MDS     |   21|
## |Vitamin C |SDF-1α         |MDS     |   18|
## |Placebo   |G-CSF          |MDS/MPN |   13|
## |Vitamin C |G-CSF          |MDS/MPN |   15|
## |Placebo   |IL-10          |MDS/MPN |   13|
## |Vitamin C |IL-10          |MDS/MPN |   15|
## |Placebo   |IL-1α          |MDS/MPN |   13|
## |Vitamin C |IL-1α          |MDS/MPN |   15|
## |Placebo   |IL-6           |MDS/MPN |   13|
## |Vitamin C |IL-6           |MDS/MPN |   15|
## |Placebo   |CXCL10 (IP-10) |MDS/MPN |   13|
## |Vitamin C |CXCL10 (IP-10) |MDS/MPN |   15|
## |Placebo   |M-CSF          |MDS/MPN |   13|
## |Vitamin C |M-CSF          |MDS/MPN |   15|
## |Placebo   |SDF-1α         |MDS/MPN |   13|
## |Vitamin C |SDF-1α         |MDS/MPN |   15|

WGCNA

Cannot get good scale-free topology WGCNA is a no go. Surprisingly little correlation among the cyotkines

##    Power SFT.R.sq  slope truncated.R.sq mean.k.  median.k. max.k.
## 1      1   0.0218 -0.159        -0.2550 1.75000 1.84000000 3.1300
## 2      2   0.0757 -2.270        -0.1740 0.55500 0.51100000 1.5100
## 3      3   0.1120 -2.460        -0.1250 0.28400 0.16500000 1.0800
## 4      4   0.3380 -5.380         0.1670 0.18100 0.07280000 0.8340
## 5      5   0.2350 -4.280         0.0173 0.12800 0.03550000 0.6700
## 6      6   0.3270 -4.290         0.1460 0.09600 0.01710000 0.5510
## 7      7   0.2910 -3.550         0.0996 0.07460 0.00763000 0.4610
## 8      8   0.3410 -4.600         0.1840 0.05940 0.00344000 0.3910
## 9      9   0.3650 -4.350         0.2140 0.04820 0.00156000 0.3340
## 10    10   0.2450 -3.560         0.2140 0.03970 0.00071200 0.2880
## 11    12   0.3180 -3.600         0.2600 0.02780 0.00015000 0.2160
## 12    14   0.3450 -3.320         0.2800 0.02000 0.00003190 0.1640
## 13    16   0.3680 -3.070         0.2980 0.01480 0.00000683 0.1250
## 14    18   0.2550 -3.100         0.6910 0.01100 0.00000147 0.0962
## 15    20   0.2720 -3.010         0.6850 0.00828 0.00000032 0.0739

PCA

Majority of variance is neither time nor treatment